code: def crf_constrained_decode(
      potentials: TensorLike,
      tag_bitmap: TensorLike,
      transition_params: TensorLike,
      sequence_length: TensorLike,
  ) -> tf.Tensor:
      """Decode the highest scoring sequence of tags under constraints.
  
      This is a function for tensor.
  
      Args:
        potentials: A [batch_size, max_seq_len, num_tags] tensor of
                  unary potentials.
        tag_bitmap: A [batch_size, max_seq_len, num_tags] boolean tensor
            representing all active tags at each index for which to calculate the
            unnormalized score.
        transition_params: A [num_tags, num_tags] matrix of
                  binary potentials.
        sequence_length: A [batch_size] vector of true sequence lengths.
      Returns:
        decode_tags: A [batch_size, max_seq_len] matrix, with dtype `tf.int32`.
                    Contains the highest scoring tag indices.
        best_score: A [batch_size] vector, containing the score of `decode_tags`.
      """
  
      filtered_potentials = crf_filtered_inputs(potentials, tag_bitmap)
      return crf_decode(
          filtered_potentials, transition_params, sequence_length
      )
  
imports: import warnings
  import numpy
  import tensorflow
  from tensorflow_addons.rnn.abstract_rnn_cell import AbstractRNNCell
  from tensorflow_addons.utils.types import TensorLike
  from typeguard import typechecked
  from typing import Optional, Tuple
label_desc: Use image node_id 13 for calling a global function with example usage: crf_constrained_decode(potentials, tag_bitmap, transition_params, sequence_length) and returns: crf_decode